from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 37.004607 |
| daal4py_KNeighborsClassifier | 0.0 | 5.0 | 15.214882 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 0.806752 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 49.451579 |
| KMeans_tall | 0.0 | 1.0 | 46.259200 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 18.599999 |
| KMeans_short | 0.0 | 0.0 | 23.607057 |
| daal4py_KMeans_short | 0.0 | 0.0 | 14.179110 |
| LogisticRegression | 0.0 | 1.0 | 9.602413 |
| daal4py_LogisticRegression | 0.0 | 1.0 | 2.601084 |
| Ridge | 0.0 | 1.0 | 0.386971 |
| daal4py_Ridge | 0.0 | 0.0 | 24.476808 |
| total | 0.0 | 34.0 | 2.280701 |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | throughput | latency | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.131 | 0.005 | 1000000 | 1000000 | 100 | brute | -1 | 1 | 6.084 | NaN | 0.991 | 0.984 | 0.512 | 0.009 | 0.257 | 0.010 | See |
| 1 | KNeighborsClassifier | predict | 30.291 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 1 | 0.000 | 0.030 | 0.991 | 0.984 | 3.843 | 0.026 | 7.882 | 0.053 | See |
| 2 | KNeighborsClassifier | predict | 0.200 | 0.018 | 1000000 | 1 | 100 | brute | -1 | 1 | 0.004 | 0.000 | 0.991 | 0.984 | 0.101 | 0.003 | 1.970 | 0.185 | See |
| 3 | KNeighborsClassifier | fit | 0.129 | 0.008 | 1000000 | 1000000 | 100 | brute | -1 | 5 | 6.183 | NaN | 0.991 | 0.984 | 0.518 | 0.015 | 0.250 | 0.018 | See |
| 4 | KNeighborsClassifier | predict | 38.494 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 0.000 | 0.038 | 0.991 | 0.984 | 3.833 | 0.017 | 10.042 | 0.044 | See |
| 5 | KNeighborsClassifier | predict | 0.199 | 0.017 | 1000000 | 1 | 100 | brute | -1 | 5 | 0.004 | 0.000 | 0.991 | 0.984 | 0.104 | 0.001 | 1.917 | 0.166 | See |
| 6 | KNeighborsClassifier | fit | 0.126 | 0.006 | 1000000 | 1000000 | 100 | brute | -1 | 100 | 6.344 | NaN | 0.991 | 0.984 | 0.495 | 0.013 | 0.255 | 0.013 | See |
| 7 | KNeighborsClassifier | predict | 38.317 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 0.000 | 0.038 | 0.991 | 0.984 | 3.883 | 0.029 | 9.868 | 0.074 | See |
| 8 | KNeighborsClassifier | predict | 0.204 | 0.011 | 1000000 | 1 | 100 | brute | -1 | 100 | 0.004 | 0.000 | 0.991 | 0.984 | 0.099 | 0.002 | 2.053 | 0.122 | See |
| 9 | KNeighborsClassifier | fit | 0.141 | 0.005 | 1000000 | 1000000 | 100 | brute | 1 | 1 | 5.679 | NaN | 0.991 | 0.984 | 0.496 | 0.014 | 0.284 | 0.013 | See |
| 10 | KNeighborsClassifier | predict | 16.047 | 0.044 | 1000000 | 1000 | 100 | brute | 1 | 1 | 0.000 | 0.016 | 0.991 | 0.984 | 3.824 | 0.038 | 4.196 | 0.043 | See |
| 11 | KNeighborsClassifier | predict | 0.198 | 0.007 | 1000000 | 1 | 100 | brute | 1 | 1 | 0.004 | 0.000 | 0.991 | 0.984 | 0.103 | 0.001 | 1.928 | 0.072 | See |
| 12 | KNeighborsClassifier | fit | 0.125 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 5 | 6.403 | NaN | 0.991 | 0.984 | 0.482 | 0.019 | 0.259 | 0.012 | See |
| 13 | KNeighborsClassifier | predict | 24.427 | 0.090 | 1000000 | 1000 | 100 | brute | 1 | 5 | 0.000 | 0.024 | 0.991 | 0.984 | 3.830 | 0.025 | 6.379 | 0.048 | See |
| 14 | KNeighborsClassifier | predict | 0.210 | 0.006 | 1000000 | 1 | 100 | brute | 1 | 5 | 0.004 | 0.000 | 0.991 | 0.984 | 0.102 | 0.002 | 2.063 | 0.071 | See |
| 15 | KNeighborsClassifier | fit | 0.131 | 0.005 | 1000000 | 1000000 | 100 | brute | 1 | 100 | 6.095 | NaN | 0.991 | 0.984 | 0.524 | 0.018 | 0.251 | 0.012 | See |
| 16 | KNeighborsClassifier | predict | 24.469 | 0.031 | 1000000 | 1000 | 100 | brute | 1 | 100 | 0.000 | 0.024 | 0.991 | 0.984 | 3.928 | 0.026 | 6.229 | 0.042 | See |
| 17 | KNeighborsClassifier | predict | 0.206 | 0.011 | 1000000 | 1 | 100 | brute | 1 | 100 | 0.004 | 0.000 | 0.991 | 0.984 | 0.106 | 0.004 | 1.935 | 0.120 | See |
| 18 | KNeighborsClassifier | fit | 0.052 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 1 | 0.305 | NaN | 0.991 | 0.984 | 0.100 | 0.004 | 0.523 | 0.029 | See |
| 19 | KNeighborsClassifier | predict | 24.877 | 0.143 | 1000000 | 1000 | 2 | brute | -1 | 1 | 0.000 | 0.025 | 0.991 | 0.984 | 0.820 | 0.024 | 30.340 | 0.914 | See |
| 20 | KNeighborsClassifier | predict | 0.021 | 0.001 | 1000000 | 1 | 2 | brute | -1 | 1 | 0.001 | 0.000 | 0.991 | 0.984 | 0.005 | 0.000 | 4.417 | 0.490 | See |
| 21 | KNeighborsClassifier | fit | 0.053 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 5 | 0.301 | NaN | 0.991 | 0.984 | 0.103 | 0.004 | 0.514 | 0.029 | See |
| 22 | KNeighborsClassifier | predict | 31.281 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 0.000 | 0.031 | 0.991 | 0.984 | 0.810 | 0.009 | 38.619 | 0.442 | See |
| 23 | KNeighborsClassifier | predict | 0.034 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 5 | 0.000 | 0.000 | 0.991 | 0.984 | 0.004 | 0.000 | 7.849 | 1.125 | See |
| 24 | KNeighborsClassifier | fit | 0.052 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 100 | 0.309 | NaN | 0.991 | 0.984 | 0.100 | 0.003 | 0.517 | 0.020 | See |
| 25 | KNeighborsClassifier | predict | 31.406 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 0.000 | 0.031 | 0.991 | 0.984 | 0.875 | 0.010 | 35.910 | 0.398 | See |
| 26 | KNeighborsClassifier | predict | 0.034 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 100 | 0.000 | 0.000 | 0.991 | 0.984 | 0.005 | 0.001 | 7.362 | 1.070 | See |
| 27 | KNeighborsClassifier | fit | 0.052 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 1 | 0.311 | NaN | 0.991 | 0.984 | 0.104 | 0.002 | 0.497 | 0.010 | See |
| 28 | KNeighborsClassifier | predict | 10.669 | 0.030 | 1000000 | 1000 | 2 | brute | 1 | 1 | 0.000 | 0.011 | 0.991 | 0.984 | 0.807 | 0.016 | 13.221 | 0.262 | See |
| 29 | KNeighborsClassifier | predict | 0.015 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 0.001 | 0.000 | 0.991 | 0.984 | 0.004 | 0.000 | 3.457 | 0.380 | See |
| 30 | KNeighborsClassifier | fit | 0.054 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 5 | 0.296 | NaN | 0.991 | 0.984 | 0.100 | 0.006 | 0.539 | 0.039 | See |
| 31 | KNeighborsClassifier | predict | 18.543 | 0.059 | 1000000 | 1000 | 2 | brute | 1 | 5 | 0.000 | 0.019 | 0.991 | 0.984 | 0.808 | 0.011 | 22.938 | 0.334 | See |
| 32 | KNeighborsClassifier | predict | 0.029 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 5 | 0.001 | 0.000 | 0.991 | 0.984 | 0.004 | 0.001 | 6.733 | 0.836 | See |
| 33 | KNeighborsClassifier | fit | 0.052 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 100 | 0.305 | NaN | 0.991 | 0.984 | 0.099 | 0.006 | 0.530 | 0.034 | See |
| 34 | KNeighborsClassifier | predict | 18.849 | 0.100 | 1000000 | 1000 | 2 | brute | 1 | 100 | 0.000 | 0.019 | 0.991 | 0.984 | 0.875 | 0.010 | 21.545 | 0.269 | See |
| 35 | KNeighborsClassifier | predict | 0.030 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 0.001 | 0.000 | 0.991 | 0.984 | 0.005 | 0.001 | 6.321 | 0.990 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | throughput | latency | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 2.796 | 0.037 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | 0.029 | NaN | 0.983 | 0.982 | 0.723 | 0.012 | 3.865 | 0.081 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.436 | 0.009 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 0.000 | 0.000 | 0.983 | 0.982 | 0.126 | 0.004 | 3.454 | 0.142 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.007 | 0.003 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 0.011 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 29.455 | 21.175 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 2.813 | 0.034 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | 0.028 | NaN | 0.983 | 0.982 | 0.760 | 0.011 | 3.700 | 0.068 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.882 | 0.013 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 0.000 | 0.001 | 0.983 | 0.982 | 0.228 | 0.005 | 3.865 | 0.105 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 0.025 | 0.000 | 0.983 | 0.982 | 0.001 | 0.001 | 4.025 | 4.172 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 2.738 | 0.077 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | 0.029 | NaN | 0.983 | 0.982 | 0.716 | 0.010 | 3.823 | 0.120 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 2.802 | 0.035 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 0.000 | 0.003 | 0.983 | 0.982 | 0.675 | 0.008 | 4.153 | 0.070 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 0.006 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 0.012 | 0.000 | 0.983 | 0.982 | 0.001 | 0.000 | 10.244 | 4.270 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 2.767 | 0.068 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | 0.029 | NaN | 0.983 | 0.982 | 0.760 | 0.010 | 3.641 | 0.101 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.759 | 0.012 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 0.000 | 0.001 | 0.983 | 0.982 | 0.133 | 0.010 | 5.724 | 0.456 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 0.074 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 3.786 | 1.802 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 2.723 | 0.035 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | 0.029 | NaN | 0.983 | 0.982 | 0.730 | 0.012 | 3.732 | 0.076 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1.507 | 0.035 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 0.000 | 0.002 | 0.983 | 0.982 | 0.224 | 0.004 | 6.725 | 0.191 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 0.060 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 4.424 | 2.164 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 2.797 | 0.064 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | 0.029 | NaN | 0.983 | 0.982 | 0.771 | 0.026 | 3.628 | 0.150 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 4.962 | 0.039 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 0.000 | 0.005 | 0.983 | 0.982 | 0.677 | 0.010 | 7.330 | 0.125 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 0.018 | 0.000 | 0.983 | 0.982 | 0.001 | 0.000 | 6.689 | 3.237 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 0.745 | 0.026 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | 0.021 | NaN | 0.983 | 0.982 | 0.496 | 0.014 | 1.502 | 0.068 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.039 | 0.009 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 0.000 | 0.000 | 0.983 | 0.982 | 0.001 | 0.000 | 47.717 | 16.541 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 0.006 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 14.983 | 6.996 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 0.746 | 0.023 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | 0.021 | NaN | 0.983 | 0.982 | 0.502 | 0.010 | 1.484 | 0.056 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.037 | 0.002 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 0.000 | 0.000 | 0.983 | 0.982 | 0.001 | 0.000 | 26.928 | 6.880 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 0.006 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 16.661 | 7.951 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 0.751 | 0.023 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | 0.021 | NaN | 0.983 | 0.982 | 0.498 | 0.013 | 1.507 | 0.060 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.061 | 0.006 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 0.000 | 0.000 | 0.983 | 0.982 | 0.007 | 0.001 | 8.563 | 1.096 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 0.006 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 13.887 | 6.661 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 0.769 | 0.018 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | 0.021 | NaN | 0.983 | 0.982 | 0.503 | 0.006 | 1.528 | 0.041 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.031 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 0.001 | 0.000 | 0.983 | 0.982 | 0.001 | 0.000 | 37.648 | 11.143 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 0.020 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 4.860 | 2.434 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 0.767 | 0.019 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | 0.021 | NaN | 0.983 | 0.982 | 0.517 | 0.011 | 1.484 | 0.049 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.034 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 0.000 | 0.000 | 0.983 | 0.982 | 0.001 | 0.000 | 28.893 | 5.399 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 0.020 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 4.661 | 2.394 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 0.767 | 0.015 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | 0.021 | NaN | 0.983 | 0.982 | 0.517 | 0.007 | 1.484 | 0.035 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.063 | 0.004 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 0.000 | 0.000 | 0.983 | 0.982 | 0.007 | 0.001 | 8.571 | 1.012 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 0.018 | 0.000 | 0.983 | 0.982 | 0.000 | 0.000 | 5.068 | 2.677 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | throughput | latency | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.616 | 0.014 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.780 | NaN | 0.002 | 30 | 0.002 | 0.319 | 0.014 | 1.927 | 0.094 | See |
| 1 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.010 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 7.738 | 3.694 | See |
| 2 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.010 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 6.641 | 3.817 | See |
| 3 | KMeans_tall | fit | 0.522 | 0.014 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.920 | NaN | 0.002 | 30 | 0.002 | 0.272 | 0.006 | 1.917 | 0.067 | See |
| 4 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.010 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 7.409 | 3.166 | See |
| 5 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.010 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 9.124 | 5.033 | See |
| 6 | KMeans_tall | fit | 7.132 | 0.082 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 3.365 | NaN | 0.002 | 30 | 0.002 | 3.980 | 0.054 | 1.792 | 0.032 | See |
| 7 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.453 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 5.710 | 1.883 | See |
| 8 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.491 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 8.087 | 4.364 | See |
| 9 | KMeans_tall | fit | 6.563 | 0.073 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30 | 3.657 | NaN | 0.002 | 30 | 0.002 | 3.754 | 0.050 | 1.749 | 0.030 | See |
| 10 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.436 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 6.281 | 2.296 | See |
| 11 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.523 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 8.735 | 3.987 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | throughput | latency | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.322 | 0.016 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 28 | 0.014 | NaN | 0.005 | 30 | 0.003 | 0.149 | 0.006 | 2.159 | 0.136 | See |
| 1 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 28 | 0.008 | 0.0 | 0.005 | 30 | 0.003 | 0.001 | 0.000 | 3.092 | 0.662 | See |
| 2 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 28 | 0.011 | 0.0 | 0.005 | 30 | 0.003 | 0.000 | 0.000 | 8.039 | 3.640 | See |
| 3 | KMeans_short | fit | 0.143 | 0.012 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30 | 0.034 | NaN | 0.005 | 30 | 0.003 | 0.069 | 0.003 | 2.063 | 0.191 | See |
| 4 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30 | 0.007 | 0.0 | 0.005 | 30 | 0.003 | 0.001 | 0.000 | 3.234 | 0.750 | See |
| 5 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30 | 0.011 | 0.0 | 0.005 | 30 | 0.003 | 0.000 | 0.000 | 7.000 | 4.182 | See |
| 6 | KMeans_short | fit | 1.058 | 0.066 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 17 | 0.129 | NaN | 0.005 | 19 | 0.003 | 0.609 | 0.048 | 1.738 | 0.174 | See |
| 7 | KMeans_short | predict | 0.003 | 0.000 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 17 | 0.261 | 0.0 | 0.005 | 19 | 0.003 | 0.002 | 0.000 | 1.905 | 0.430 | See |
| 8 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 17 | 0.465 | 0.0 | 0.005 | 19 | 0.003 | 0.000 | 0.000 | 8.244 | 4.093 | See |
| 9 | KMeans_short | fit | 0.296 | 0.033 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 21 | 0.568 | NaN | 0.005 | 26 | 0.003 | 0.331 | 0.032 | 0.894 | 0.133 | See |
| 10 | KMeans_short | predict | 0.003 | 0.000 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 21 | 0.262 | 0.0 | 0.005 | 26 | 0.003 | 0.002 | 0.000 | 1.977 | 0.382 | See |
| 11 | KMeans_short | predict | 0.002 | 0.001 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | 21 | 0.378 | 0.0 | 0.005 | 26 | 0.003 | 0.000 | 0.000 | 10.061 | 8.111 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | throughput | latency | accuracy_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 15.449 | 0.046 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | [-0.07637218] | NaN | 0.26 | 15.528 | 0.187 | 0.995 | 0.012 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 2.1925497155176576 | 0.0 | 0.26 | 0.000 | 0.000 | 0.847 | 0.375 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 8.225332995412497 | 0.0 | 0.26 | 0.000 | 0.000 | 0.276 | 0.286 | See |
| 3 | LogisticRegression | fit | 1.186 | 0.089 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | [1.75386157] | NaN | 0.26 | 1.289 | 0.023 | 0.920 | 0.071 | See |
| 4 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 3.4158805052975714 | 0.0 | 0.26 | 0.004 | 0.000 | 0.568 | 0.089 | See |
| 5 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 61.246035288228306 | 0.0 | 0.26 | 0.001 | 0.000 | 0.154 | 0.079 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | deprecated |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | throughput | latency | r2_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 2.734 | 0.055 | 100000 | 100000 | 1000 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | NaN | 0.293 | NaN | 1.0 | 1.580 | 0.023 | 1.730 | 0.043 | See |
| 1 | Ridge | predict | 0.001 | 0.000 | 100000 | 1000 | 1000 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | NaN | 10.164 | 0.0 | 1.0 | 0.002 | 0.002 | 0.429 | 0.431 | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 100000 | 1 | 1000 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | NaN | 83.814 | 0.0 | 1.0 | 0.000 | 0.000 | 0.674 | 0.486 | See |
| 3 | Ridge | fit | 1.228 | 0.026 | 1000000 | 1000000 | 100 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | NaN | 0.651 | NaN | 1.0 | 0.340 | 0.010 | 3.611 | 0.131 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | NaN | 4.772 | 0.0 | 1.0 | 0.000 | 0.000 | 0.690 | 0.417 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | NaN | 9.168 | 0.0 | 1.0 | 0.000 | 0.000 | 0.619 | 0.464 | See |
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